The Impact of Selective Dopamine D2, D3 and D4 Ligands on the Rat Gambling Task
Bibliographic record
Abstract
Gambling is an addictive disorder with serious societal and personal costs. To-date, there are no approved pharmacological treatments for gambling disorder. Evidence suggests a role for dopamine in gambling disorder and thus may provide a therapeutic target. The present study therefore aimed to investigate the effects of selective antagonists and agonists of D2, D3 and D4 receptors in a rodent analogue of the Iowa gambling task used clinically. In this rat gambling task (rGT), animals are trained to associate different response holes with different magnitudes and probabilities of food pellet rewards and punishing time-out periods. As in the Iowa gambling task, the optimal strategy is to avoid the tempting high-risk high-reward options, and instead favor those linked to smaller per-trial rewards but also lower punishments, thereby maximizing the amount of reward earned over time. Administration of those selective ligands did not affect decision making under the rGT. Only the D4 drug had modest effects on latency measures suggesting that D4 may contribute in some ways to decision making under this task.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".